Pedrosa de Barros Nuno, Slotboom Johannes
University of Bern, Switzerland; Support Center for Advanced Neuroimaging, Inselspital, Bern, Switzerland.
Support Center for Advanced Neuroimaging, Inselspital, Bern, Switzerland.
Anal Biochem. 2017 Jul 15;529:98-116. doi: 10.1016/j.ab.2017.01.017. Epub 2017 Jan 21.
The quality of MR-Spectroscopy data can easily be affected in in vivo applications. Several factors may produce signal artefacts, and often these are not easily detected, not even by experienced spectroscopists. Reliable and reproducible in vivo MRS-data requires the definition of quality requirements and goals, implementation of measures to guarantee quality standards, regular control of data quality, and a continuous search for quality improvement. The first part of this review includes a general introduction to different aspects of quality management in MRS. It is followed by the description of a series of tests and phantoms that can be used to assure the quality of the MR system. In the third part, several methods and strategies used for quality control of the spectroscopy data are presented. This review concludes with a reference to a few interesting techniques and aspects that may help to further improve the quality of in vivo MR-spectra.
在活体应用中,磁共振波谱(MR-Spectroscopy)数据的质量很容易受到影响。有几个因素可能会产生信号伪影,而且这些伪影往往不易被检测到,即使是经验丰富的波谱学家也难以察觉。可靠且可重复的活体磁共振波谱数据需要定义质量要求和目标,实施确保质量标准的措施,定期控制数据质量,并持续寻求质量改进。本综述的第一部分包括对磁共振波谱质量管理不同方面的总体介绍。接下来描述了一系列可用于确保MR系统质量的测试和体模。在第三部分,介绍了用于波谱数据质量控制的几种方法和策略。本综述最后提及了一些可能有助于进一步提高活体MR谱质量的有趣技术和方面。